Job description

Purpose: This position is responsible for building, deploying, and maintaining the ML models that power Floor & Decor's digital customer experience across flooranddecor.com, FND apps, and omni-channel digital shopping tools. Areas of work will include product search and discovery, personalization and recommendations, product data enrichment, and AI-assisted shopping. Working cross-functionally with Ecommerce Product, Engineering & Analytics, Data Engineering, Merchandising, and Digital Marketing, this role owns models end to end, from problem definition through production deployment, monitoring, and continuous improvement. In partnership with the Lead Data Scientist, AI/ML, this role helps set the standard for how digital machine learning is built and measured, with success defined by measurable improvement in how customers find, evaluate, and choose products. Minimum Eligibility Requirements: • Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field (Master's or PhD a plus); relevant experience can be substituted for the required education on the basis of one calendar year of experience for one academic year of education. • 5+ years of experience in data science or machine learning, or an equivalent combination of education and experience sufficient to perform the essential functions of the job, as determined by the company. • Experience building machine learning for live, customer-facing digital products such as search, recommendations, ranking, personalization, or ads, in eCommerce, marketplaces, media, or similar environments. • Track record of taking multiple models into production and owning them after launch, including monitoring, troubleshooting, and retraining. • Depth in search and ranking or in recommendations and personalization, with the breadth to contribute across both. • Applied experience with natural language processing, embeddings, and large language models, including retrieval and reranking, and evaluating their output. • Expert proficiency in Python and SQL, with production-quality coding practices. • Hands-on experience with ML lifecycle practices and tooling, including automated training and scoring pipelines, model deployment, and monitoring. • Rigor in model evaluation and online experimentation (A/B testing) on digital products. • Proficiency with AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate exploration, modeling, and engineering. • Comfortable working while the roadmap and platforms take shape: frames ambiguous problems, starts simple, and adds complexity only when it pays off. • Strong communication skills, with the ability to explain model behavior, tradeoffs, and expected impact to product, engineering, and business leaders. Preferred Qualifications: • Experience helping build an emerging ML function: establishing the practices, tooling, and production patterns a growing team builds on. • Databricks on Azure, PySpark, and CI/CD for ML, including MLflow, model registry, model serving, and feature stores. • Experience extending, evaluating, or migrating commercial search or personalization platforms (e.g., Bloomreach, Constructor, Algolia, Dynamic Yield, Salesforce Personalization, Salesforce Commerce Cloud). • Semantic search, retrieval-augmented generation (RAG), or computer vision applied to product discovery. • eCommerce or omnichannel retail experience, ideally in high-consideration, project-based categories (home improvement, furniture, home décor). • Experience with LLM-based agents or tool-using workflows. • Experience with clickstream and customer behavioral data at scale. • Experience with causal inference methods for measuring impact. • Experience mentoring other data scientists or serving as technical lead on a multi-person ML effort. Essential Job Functions: • Build and improve ML models for product search and discovery, using Floor & Decor's proprietary signals (customer behavior, store-level availability, local demand) to help customers find the right products faster. • Develop personalization and recommendation models across site and app, including "complete the project" recommendations and session-based models for anonymous and infrequent shoppers. • Apply LLMs and computer vision to enrich product attributes at catalog scale, improving search, filtering, recommendations, and product feeds, with quality controls appropriate for technical product specifications. • Partner with the Lead Data Scientist, AI/ML on conversational shopping and AI-assisted project guidance, owning retrieval quality and evaluation, including offline evaluation sets, and monitoring of quality, cost, latency, and safety. • Build durable ML assets (enriched product data, embeddings, evaluation sets) that carry across eCommerce platform and vendor changes. • Lead quantitative evaluation of search and personalization vendors using Floor & Decor's own data; recommend where platform configuration is sufficient and where proprietary models create defensible value. • Own models in production on Databricks, delivering documented outputs that Ecommerce and IT Engineering integrate into the site, app, and vendor platforms; monitor performance and own retraining and troubleshooting. • Help build out ML capabilities on Databricks as needs expand, and, with the Lead Data Scientist, AI/ML, define team ML engineering standards built to scale as the team grows. • Partner with Data Engineering, Product, and Engineering on the data and event tracking needed to train and measure models. • Design and analyze A/B tests for model-driven features, measure incremental impact on conversion, average order value, and engagement, and confirm that offline model gains translate into online results. Standard digital performance reporting is owned by Ecommerce Analytics. • Inform the digital data science roadmap, set jointly by Ecommerce Product and Data Science leadership, by sizing opportunities, assessing feasibility, and communicating what a model will and won't do. • Serve as technical lead for digital ML: guide the work of the Data Scientist, Digital, raise the team's technical bar through design and code reviews, and support recruiting and hiring. • Maintain clear documentation of methodologies, model assumptions, and limitations to ensure reproducibility and continuity. • Stay abreast of developments in search, recommender systems, and applied generative AI, and bring relevant advances into Floor & Decor's practice. • Be compliant with all appropriate Privacy Preferences, Responsible AI, and Security protocols, including guardrails for customer-facing generative AI. Working Conditions (travel & environment) • Travel may be required including air and car travel (typically less than 10%). • The noise level in the work environment is typically quiet to moderate. Note: Floor & Decor considers all applicants for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, medical condition, pregnancy, marital or familial status, veteran status, or based on any other class protected by applicable federal, state, or local law. Floor & Decor also provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law. This job description does not constitute an employment agreement between the employer and the employee and is subject to change by the employer at its sole discretion. Benefits & Rewards Bonus opportunities & career advancement opportunities at every level Programs that help you reach your financial goals: 401k with company match, Employee Stock Purchase Plan, and Referral Bonus Program Medical, Dental, Vision, Life, and other Insurance Plans (subject to eligibility criteria) Work-life balance, including: • Paid vacation and sick time for eligible associates • Paid holidays plus a personal holiday • Paid Volunteer Time Off that starts on Day 1 Equal Employment Opportunity Floor & Decor provides equal employment opportunities to all associates and applicants without regard to age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, disability, veteran status, genetic information, ethnicity, citizenship, or any other category protected by law. This policy applies to all areas of employment, including recruitment, testing, screening, hiring, selection for training, upgrading, transfer, demotion, layoff, discipline, termination, compensation, benefits and all other privileges, terms and conditions of employment. This policy and the law prohibit employment discrimination against any associate or applicant on the basis of any legally protected status outlined above.

Requirements

Must-haves

5+ years of experience in data science or machine learning, or an equivalent combination of education and experience sufficient to perform the essential functions of the job, as determined by the company.
Experience building machine learning for live, customer-facing digital products such as search, recommendations, ranking, personalization, or ads, in eCommerce, marketplaces, media, or similar environments.
Track record of taking multiple models into production and owning them after launch, including monitoring, troubleshooting, and retraining.
Depth in search and ranking or in recommendations and personalization, with the breadth to contribute across both.
Applied experience with natural language processing, embeddings, and large language models, including retrieval and reranking, and evaluating their output.
Expert proficiency in Python and SQL, with production-quality coding practices.
Hands-on experience with ML lifecycle practices and tooling, including automated training and scoring pipelines, model deployment, and monitoring.
Rigor in model evaluation and online experimentation (A/B testing) on digital products.
Proficiency with AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate exploration, modeling, and engineering.
Comfortable working while the roadmap and platforms take shape: frames ambiguous problems, starts simple, and adds complexity only when it pays off.
Strong communication skills, with the ability to explain model behavior, tradeoffs, and expected impact to product, engineering, and business leaders.
Build and improve ML models for product search and discovery, using Floor & Decor's proprietary signals (customer behavior, store-level availability, local demand) to help customers find the right products faster.
Develop personalization and recommendation models across site and app, including "complete the project" recommendations and session-based models for anonymous and infrequent shoppers.
Apply LLMs and computer vision to enrich product attributes at catalog scale, improving search, filtering, recommendations, and product feeds, with quality controls appropriate for technical product specifications.

Nice-to-haves

Experience helping build an emerging ML function: establishing the practices, tooling, and production patterns a growing team builds on.
Databricks on Azure, PySpark, and CI/CD for ML, including MLflow, model registry, model serving, and feature stores.
Experience extending, evaluating, or migrating commercial search or personalization platforms (e.g., Bloomreach, Constructor, Algolia, Dynamic Yield, Salesforce Personalization, Salesforce Commerce Cloud).
Semantic search, retrieval-augmented generation (RAG), or computer vision applied to product discovery.
eCommerce or omnichannel retail experience, ideally in high-consideration, project-based categories (home improvement, furniture, home décor).
Experience with LLM-based agents or tool-using workflows.
Experience with clickstream and customer behavioral data at scale.
Experience with causal inference methods for measuring impact.
Experience mentoring other data scientists or serving as technical lead on a multi-person ML effort.
Bonus opportunities & career advancement opportunities at every level

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlaimachine learningpythonsqlazureci/cdllm

Platform: phenom
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k